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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31353?offset=310</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27845/cnidaria-fast-reference-free-phylogenomic-clustering</guid>
	<pubDate>Thu, 16 Jun 2016 17:55:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27845/cnidaria-fast-reference-free-phylogenomic-clustering</link>
	<title><![CDATA[CNIDARIA: fast, reference-free phylogenomic clustering]]></title>
	<description><![CDATA[<p>Motivation: Identification of biological specimens is a major requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but these do not scale to arbitrarily large genomes and arbitrarily large phylogenetic distances.</p>
<p>Results: We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on ge-nome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100% accuracy at supra-species level and 78% accuracy for species level.</p>
<p>Availability and Implementation: Cnidaria is written in C++ and Python and is available at http://www.ab.wur.nl/cnidaria.</p>
<p>Contact: Saulo Aflitos - sauloal@gmail.com</p>
<p>Supplementary information: Supplementary data are available at Bioinformatics online.</p><p>Address of the bookmark: <a href="https://github.com/sauloal/cnidaria/wiki" rel="nofollow">https://github.com/sauloal/cnidaria/wiki</a></p>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32152/upsetr-shiny-app</guid>
	<pubDate>Fri, 14 Apr 2017 06:19:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32152/upsetr-shiny-app</link>
	<title><![CDATA[UpSetR Shiny App!]]></title>
	<description><![CDATA[<p>UpSetR generates static&nbsp;<a href="http://vcg.github.io/upset/?dataset=0&amp;duration=1000&amp;orderBy=subsetSize&amp;grouping=groupByIntersectionSize&amp;selection=">UpSet plots</a>. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.</p>
<h4>To begin, input your data using one of the three input styles.</h4>
<ol>
<li>"File" takes a correctly formatted.csv file.</li>
<li>"List" takes up to 6 different lists that contain unique elements, similar to that used in the web applications BioVenn&nbsp;<a href="http://www.biomedcentral.com/content/pdf/1471-2164-9-488.pdf">(Hulsen et al., 2008)</a>&nbsp;and jvenn&nbsp;<a href="http://www.biomedcentral.com/content/pdf/1471-2105-15-293.pdf">(Bardou et al., 2014)</a></li>
<li>"Expression" takes the input used by the venneuler R package&nbsp;<a href="https://cran.r-project.org/web/packages/venneuler/venneuler.pdf">(Wilkinson, 2015)</a></li>
</ol><p>Address of the bookmark: <a href="https://gehlenborglab.shinyapps.io/upsetr/" rel="nofollow">https://gehlenborglab.shinyapps.io/upsetr/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28168/sam-flags</guid>
	<pubDate>Wed, 29 Jun 2016 15:38:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28168/sam-flags</link>
	<title><![CDATA[SAM flags]]></title>
	<description><![CDATA[<p>Decoding SAM flags</p>
<p>This utility makes it easy to identify what are the properties of a read based on its SAM flag value, or conversely, to find what the SAM Flag value would be for a given combination of properties.</p>
<p>To decode a given SAM flag value, just enter the number in the field below. The encoded properties will be listed under Summary below, to the right.</p><p>Address of the bookmark: <a href="https://broadinstitute.github.io/picard/explain-flags.html" rel="nofollow">https://broadinstitute.github.io/picard/explain-flags.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32483/cla-contig-layout-authenticator</guid>
	<pubDate>Fri, 05 May 2017 05:58:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32483/cla-contig-layout-authenticator</link>
	<title><![CDATA[CLA: Contig-Layout-Authenticator]]></title>
	<description><![CDATA[<p><span>To improve upon the shortcomings associated with the construction of draft genomes with Illumina paired-end sequencing, we developed Contig-Layout-Authenticator (CLA). The CLA pipeline can scaffold reference-sorted contigs based on paired reads, resulting in better assembled genomes. Moreover, CLA also hints at probable misassemblies and contaminations, for the users to cross-check before constructing the consensus draft. The CLA pipeline was designed and trained extensively on various bacterial genome datasets for the ordering and scaffolding of large repetitive contigs. The tool has been validated and compared favorably with other widely-used scaffolding and ordering tools using both simulated and real sequence datasets. CLA is a user friendly tool that requires a single command line input to generate ordered scaffolds.</span></p>
<p><span>Script&nbsp;https://sourceforge.net/projects/c-l-authenticator/files/</span></p><p>Address of the bookmark: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459" rel="nofollow">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</guid>
	<pubDate>Fri, 30 Sep 2016 10:22:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29276/murasaki</link>
	<title><![CDATA[Murasaki]]></title>
	<description><![CDATA[<p>Murasaki is an anchor alignment program that is</p>
<ul style="margin-left: 16px;">
<li>exteremely fast (17 CPU hours for whole Human x Mouse genome (with 40 nodes: 35 wall minutes), or 8 mammals in 21 CPU hours (42 wall minutes))</li>
<li>scalable (Arbitrarily parallelizable across multiple nodes using MPI)</li>
<li>memory efficient. (Even a single node with 16GB of ram can handle over 1Gbp of sequence)</li>
<li>unlimited by pattern length or selection</li>
<li>repeat tolerant</li>
</ul>
<p><img src="http://murasaki.dna.bio.keio.ac.jp/9mammals-small.png" width="500" height="375" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki" rel="nofollow">http://murasaki.dna.bio.keio.ac.jp/wiki/index.php?Murasaki</a></p>]]></description>
	<dc:creator>Anjana</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</guid>
	<pubDate>Wed, 20 Dec 2017 08:49:55 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34715/delta-a-new-web-based-3d-genome-visualization-and-analysis-platform</link>
	<title><![CDATA[Delta: a new Web-based 3D genome visualization and analysis platform]]></title>
	<description><![CDATA[<p><em>Delta</em><span>&nbsp;is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes.&nbsp;</span><em>Delta</em><span>&nbsp;takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome.&nbsp;</span><em>Delta</em><span>features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.</span></p>
<p>https://github.com/zhangzhwlab/delta</p><p>Address of the bookmark: <a href="https://github.com/zhangzhwlab/delta" rel="nofollow">https://github.com/zhangzhwlab/delta</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29305/miro-mirna-omics</guid>
	<pubDate>Tue, 04 Oct 2016 14:50:48 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29305/miro-mirna-omics</link>
	<title><![CDATA[MIRO : miRNA omics]]></title>
	<description><![CDATA[<p><span>The MIRO (the miRNA omics) pipeline is a flexible and powerful tool for the analysis of miRNA (or more generall short RNA) expression using short-read deep sequencing data. In its present implementation MIRO is especially adapted for the analysis of reads generated with the Illumina sequencing platform. MIRO allows to preprocess the Solexa-reads, map them flexibly to several reference genomes using one of four different mappers, create differential gene (miRNA) expression profiles and cluster reads using one of several algorithm. MIRO output is furthermore compatible with software such as genome browsers and miRDeep.</span></p><p>Address of the bookmark: <a href="http://seq.crg.es/download/software/Miro/" rel="nofollow">http://seq.crg.es/download/software/Miro/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/35384/mgcv-the-microbial-genomic-context-viewer-for-comparative-genome-analysis</guid>
	<pubDate>Mon, 29 Jan 2018 04:55:46 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/35384/mgcv-the-microbial-genomic-context-viewer-for-comparative-genome-analysis</link>
	<title><![CDATA[MGcV: the microbial genomic context viewer for comparative genome analysis]]></title>
	<description><![CDATA[<p><span>MGcV is an interactive web-based visalization tool tailored to facilitate small scale genome analysis. To start using MGcV:</span></p>
<ol>
<li>Supply your genes/genomic segments/phylogenetic tree of interest in the input-box by
<ul>
<li>selecting the type of identifier and pasting identifiers (one per line)</li>
<li><em><strong>or</strong></em>&nbsp;by using the&nbsp;<a>gene ID search tool</a></li>
<li><em><strong>or</strong></em>&nbsp;with the&nbsp;<a>BLAST search tool</a></li>
</ul>
</li>
<li>Click "Visualize context".</li>
</ol>
<p><span>Consult the&nbsp;</span><a href="http://mgcv.cmbi.ru.nl/help.html" target="_blank">documentation</a><span>&nbsp;to learn more about MGcV.</span></p><p>Address of the bookmark: <a href="http://mgcv.cmbi.ru.nl/" rel="nofollow">http://mgcv.cmbi.ru.nl/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29915/professor-all-levels-in-bioinformatics-and-computational-biology</guid>
  <pubDate>Tue, 22 Nov 2016 05:43:38 -0600</pubDate>
  <link></link>
  <title><![CDATA[Professor (all levels) in Bioinformatics and Computational Biology]]></title>
  <description><![CDATA[
<p>King Abdullah University of Science and Technology (KAUST) (kaust.edu.sa) is seeking a highly motivated and skilled faculty member for the Bioinformatics track whose research focuses on development of methods and tools for Bioinformatics and Computational Biology.<br />KAUST is an international, graduate-level research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Located on the shores of the Red Sea in Saudi Arabia, KAUST offers superb research facilities, generous assured research funding, and internationally competitive salaries, attracting top international faculty, scientists, engineers, and students to conduct fundamental and goal-oriented research to address the world’s pressing scientific and technological challenges in the areas of food, water, energy, and the environment.<br />The successful applicant is expected to develop world-leading research in domain of bioinformatics/computational biology with focus on development of novel computational approaches for efficient and accurate methods of analyzing biological phenomena at molecular level. The faculty member will be part of the Computational Bioscience Research Center (CBRC) within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. The position will remain open until filled.<br /> <br />Requirements:<br /> <br />PhD or equivalent in a Computer Science, Mathematics or Engineering discipline. Candidates should be well-established within the research field relevant to the position grade. They should demonstrate original research and experience at the highest international level.<br /> <br />Responsibilities and tasks:<br /> <br />Research competence in the following areas is preferred:<br />Analysis of next generation sequencing (NGS) and other ‘omics’ data (e.g. CAGE, ChIP-Seq, DHS, RNA-Seq, Ribo-Seq, proteomic, metabolic and NMR spectra, etc.).<br />Signaling, regulatory and metabolic pathways analysis.<br />Development of tools (web-based and standalone) suited for efficient computational biology/bioinformatics.<br /> <br /> <br />Visit cemse.kaust.edu.sa to apply.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</guid>
	<pubDate>Wed, 21 Feb 2024 06:19:41 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44472/pipesnake-bioinformatics-best-practice-analysis-pipeline-for-phylogenomic-reconstruction</link>
	<title><![CDATA[pipesnake: bioinformatics best-practice analysis pipeline for phylogenomic reconstruction]]></title>
	<description><![CDATA[<p dir="auto"><span>ausarg/pipesnake</span>&nbsp;is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.</p>
<p dir="auto">The pipeline is built using&nbsp;<a href="https://www.nextflow.io/">Nextflow</a>, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The&nbsp;<a href="https://www.nextflow.io/docs/latest/dsl2.html">Nextflow DSL2</a>&nbsp;implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.</p><p>Address of the bookmark: <a href="https://github.com/AusARG/pipesnake" rel="nofollow">https://github.com/AusARG/pipesnake</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

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